Motion Estimation is an essential process in many video coding standards like MPEG-2, H.264/AVC and HEVC. Despite Motion Estimation has been used at the encoder, it is expected to be used in future consumer devices in the distributed video coding architectures. But the Motion Estimation itself consumes more than 50% coding complexity or time to encode. To reduce the computation time, many fast Motion Estimation Algorithms were proposed and implemented. The present paper proposes a new fast ME algorithm which outperforms the fast ME algorithm implemented in HEVC reference software HM.

This paper, proposes improvements to TZ search motion estimation algorithm with reference to its implementation in JMVC reference software. In TZS, the search patterns that are implemented are 8-point diamond and 8-point square. When these are replaced with hexagonal patterns, there is a large improvement in encoding time. Further, the TZS algorithm is improved by changing the searching threshold for each grid in the search area. Simulation results show that the overall encoding time can be reduced by almost 50% compared to TZS algorithm, while maintaining the same PSNR and bitrate.

Very often in signal and video processing applications, there is a strong demand for accessing the same memory location through multiple read ports. For video processing applications like Motion Estimation (ME), the same pixel, as part of the search window, is used in many calculations of SAD (Sum of Absolute Differences). In a design for such applications, there is a trade-off between number of effective gates used and the maximum operating frequency. Particularly, in FPGAs, the existing block RAMs do not support multiple port access and the replication of DRAM (Distributed RAM) leads to significant increase in the number of used CLBs(Configurable Logic Blocks). The present paper analyses different approaches that were previously used to solve this problem (same location reading)and proposes an effective solution by using an efficient combinational logic to synchronously and simultaneously read the video pixel memory data through multiple read-ports.

Video compression is required in applications like video network communications, video conference, broadcasting, live streaming and video storage. H.265/HEVC is the latest video compression standard, jointly developed by JCT-VC that provides the highest compression efficiency without significant loss in original video source quality. Among all the tools in HEVC encoder, Motion Estimation (ME) is one of the most complex tasks. The present paper analyses the ME algorithm present in HEVC standard reference software and proposes two improvements to the algorithm. Our results show a decrease on the computational complexity by almost 30% with negligible loss in the video quality.

Motion estimation (ME) is one of the critical and most time consuming tasks in video coding. The increase of block size to 64x64 and introduction of asymmetric motion partitioning (AMP) in HEVC makes variable block size motion estimation more complex and therefore requires specific hardware architecture for real time implementation. The ME process includes the calculation of SAD (Sum of Absolute Difference) of two blocks, the current and the reference blocks. The present paper proposes low complexity SAD (Sum of Absolute Difference) architecture for ME of HEVC video encoder, which is able to exploit and optimize parallelism at various levels. The proposed architecture was implemented in FPGA, and compared with other non-parallel SAD architectures. Synthesis results show that the proposed architecture takes fewer resources in FPGA when compared with results from non-parallel architectures and other contributions.

This work explores the highly advantageous cost/benefit relation presented by low discrepancy sequences as a pixel-decimation technique to improve the block estimation performance in the H.264/AVC. The proposed method is able to efficiently estimate motion vectors for block matching algorithms present in the H.264 by using latticed decimation sampled according to the Van Der Corput-Halton sequences. This paper further explores motion estimation within the H.264, validating it with real-case-video-encoding scenarios. The results have shown that this technique incorporated to the H.264 is generally more efficient than other decimation techniques used in similar conditions.

The estimation of motion of multi-camera systems is one of the most important tasks in computer vision research. Recently, some issues have been raised about general camera models and multi-camera systems. Using many cameras as a single camera is studied [60], and the epipolar geometry constraints of general camera models is theoretically derived. Methods for calibration, including a self-calibration method for general camera models, are studied [78, 62]. Multi-camera systems are an example of practically implementable general camera models and they are widely used in many applications nowadays because of both the low cost of digital charge-coupled device (CCD) cameras and the high resolution of multiple images from the wide ﬁeld of views. To our knowledge, no research has been conducted on the relative motion of multi-camera systems with non-overlapping views to obtain a geometrically optimal solution. ¶ In this thesis, we solve the camera motion problem for multi-camera systems by using linear methods and convex optimization techniques, and we make ﬁve substantial and original contributions to the ﬁeld of computer vision. ...; yes

Arterial motion estimation in ultrasound (US) sequences is a hard task due to noise and discontinuities in the signal derived from US artifacts. Characterizing the mechanical properties of the artery is a promising novel imaging technique to diagnose various cardiovascular pathologies and a new way of obtaining relevant clinical information, such as determining the absence of dicrotic peak, estimating the Augmentation Index (AIx), the arterial pressure or the arterial stiffness. One of the advantages of using US imaging is the non-invasive nature of the technique unlike Intra Vascular Ultra Sound (IVUS) or angiography invasive techniques, plus the relative low cost of the US units. In this paper, we propose a semi rigid deformable method based on Soft Bodies dynamics realized by a hybrid motion approach based on cross-correlation and optical flow methods to quantify the elasticity of the artery. We evaluate and compare different techniques (for instance optical flow methods) on which our approach is based. The goal of this comparative study is to identify the best model to be used and the impact of the accuracy of these different stages in the proposed method. To this end, an exhaustive assessment has been conducted in order to decide which model is the most appropriate for registering the variation of the arterial diameter over time. Our experiments involved a total of 1620 evaluations within nine simulated sequences of 84 frames each and the estimation of four error metrics. We conclude that our proposed approach obtains approximately 2.5 times higher accuracy than conventional state-of-the-art techniques.

Motion estimation is the most time-consuming subsystem in a video codec. Thus, more efficient methods of motion estimation should be investigated. Real video sequences usually exhibit a wide-range of motion content as well as different degrees of detail, which become particularly difficult to manage by typical block-matching algorithms. Recent developments in the area of motion estimation have focused on the adaptation to video contents. Adaptive thresholds and multi-pattern search algorithms have shown to achieve good performance when they success to adjust to motion characteristics. This paper proposes an adaptive algorithm, called MCS, that makes use of an especially tailored classifier that detects some motion cues and chooses the search pattern that best fits to them. Specifically, a hierarchical structure of binary linear classifiers is proposed. Our experimental results show that MCS notably reduces the computational cost with respect to an state-of-the-art method while maintaining the quality

In this paper, a low-complexity motion-based saliency map estimation method for perceptual video coding is proposed. The method employs a camera motion compensated vector map computed by means of a hierarchical motion estimation (HME) procedure and a Restricted Affine Transformation (RAT)-based modeling of the camera motion. To allow for a computationally efficient solution, the number of layers of the HME has been restricted and the potential unreliable motion vectors due to homogeneous regions have been detected and specially managed by means of a smooth block detector. Special care has been taken of the smoothness of the resulting compensated camera motion vector map to avoid unpleasant artifacts in the perceptually-coded sequence, by including a final post-processing based on morphological filtering. The proposed saliency map has been both visually and subjectively assessed showing quality improvements when used as a part of the H.264/AVC standard codec at medium-to-low bitrates.; Regional project CCG10-UC3M/TIC-5570 from Comunidad Autónoma de Madrid / University Carlos III Madrid; Proceeding of: 2nd National Conference on Telecommunications (CONATEL), Arequipa, 17-20 May 2011

The motion estimation (ME) process used in the H.264/AVC reference software is based on minimizing a cost function that involves two terms (distortion and rate) that are properly balanced through a Lagrangian parameter, usually denoted as lambda(motion). In this paper we propose an algorithm to improve the conventional way of estimating lambda(motion) and, consequently, the ME process. First, we show that the conventional estimation of lambda(motion) turns out to be significantly less accurate when ME-compromising events, which make the ME process to perform poorly, happen. Second, with the aim of improving the coding efficiency in these cases, an efficient algorithm is proposed that allows the encoder to choose between three different values of lambda(motion) for the Inter 16x16 partition size. To be more precise, for this partition size, the proposed algorithm allows the encoder to additionally test lambda(motion) = 0 and lambda(motion) arbitrarily large, which corresponds to minimum distortion and minimum rate solutions, respectively. By testing these two extreme values, the algorithm avoids making large ME errors. The experimental results on video segments exhibiting this type of ME-compromising events reveal an average rate reduction of 2.20% for the same coding quality with respect to the JM15.1 reference software of H.264/AVC. The algorithm has been also tested in comparison with a state-of-the-art algorithm called context adaptive Lagrange multiplier. Additionally...

We present a motion estimation algorithm for multi-camera systems consisting of more than one calibrated camera securely attached on a moving object. So, they move all together, but do not require to have overlapping views across the cameras. The geometri

This paper introduces a novel, robust approach for 6DOF motion estimation of a multi-camera system with non-overlapping views. The proposed approach is able to solve the pose estimation, including scale, for a two camera system with non-overlapping views.

This is the author accepted manuscript. The final version is available from IEEE via http://dx.doi.org/10.1109/ICIP.2014.7025259; In this paper, we propose a Generalized Kalman Filtered Compressive Sensing (Generalized-KFCS) framework to reconstruct a video sequence, which relaxes the assumption of a slowly changing sparsity pattern in Kalman Filtered Compressive Sensing [1, 2, 3, 4]. In the proposed framework, we employ motion estimation to achieve the estimation of the state transition matrix for the Kalman filter, and then reconstruct the video sequence via the Kalman filter in conjunction with compressive sensing. In addition, we propose a novel method to directly apply motion estimation to compressively sensed samples without reconstructing the video sequence. Simulation results demonstrate the superiority of our algorithm for practical video reconstruction.; This work was partially supported by EPSRC Research Grant EP/K033700/1, the Fundamental Research Funds for the Central Universities (No. 2014JBM149), and the Scientific Research Foundation for the Returned Overseas Chinese Scholars (of State Education Ministry).

Video compression techniques remove temporal redundancy among frames and enable high compression efficiency in coding systems. Reduction of temporal redundancy is achieved by motion compensation. In turn, motion compensation requires motion estimation. Block matching is perhaps the most reliable and robust technique for motion estimation in video coding. However, block matching is computational expensive. Different approaches have been proposed in order to improve block matching motion estimation accuracy and efficiency. In this paper a block-matching strategy for motion estimation is introduced. In the proposed approach the size of matching block is adapted according to the variability of the matching areas. That is, the block size is constrained by variations of the image intensity. The variability is assessed using two variability measures: the variance and the mean absolute deviation. Results of computer experiments aimed at validating the performance of the proposed approach are also reported.